As is known in the art, molecular imaging refers to a multi-discipline at the intersection of molecular biology and in vivo imaging. This provides molecular level of information in a noninvasive manner. Preclinical research and development is no doubt the most critical application of molecular imaging. Highly available live information from molecular imaging for observation of functional activity between organs is very helpful for screening and investigation of new drugs.
There are many different image modalities of molecular imaging. Among the modalities, Computed Tomography (CT), Positron Emission Tomography (PET), Single Photon Emission Computed Tomography (SPECT), In Vivo Bioluminescence System and Magnetic Resonance Imaging (MRI) are with the best image resolution and are among the most important modalities. Normally these modalities are with high sensitivity and provide micron level of resolution especially nuclear medicine modalities such as PET and SPECT by using trace level radiopharmaceuticals. Quantization of molecular imaging information is then becoming an important issue since these radiopharmaceuticals are not only going to be used in animals, but also to the human. Pharmacokinetic, bio-distribution, and radiation dosimetry can then be obtained without sacrificing animals or invasive surgery to the human.
To better quantization of images generated by molecular imaging modalities, precise three dimension (3D) segmentation of the target is required to be provided. Taking SPECT/CT image quantization as an example, quantization of a specified segmentation from SPECT planar can vary from −14%˜50%, quantization of SPECT can vary from −40%˜52%, while SPECT/CT can vary from −22%˜24%. Although the above results are statistically meaningful for scientific research, the results are still worse than imaging of phantom and its quantization. The major reason is how region-of-interest (ROI) or VOI is defined especially its size and location. In the conventional method, sphere and cube for VOI, circle and square for ROI, and segmentation defined by free hand are provided to localize the target. Some commercial software provides automatic VOI/ROI selection by definition of threshold. However, threshold selection is based on contrast of the image (normally presented by color of each channel such as red, green, and blue) and can be confounded by noisy signals or signals coming from conjunction organs therefore the variation can be enlarged. Freehand definition of VOI/ROI made by professional molecular imaging experts always gets the best quality of quantization. However, better resolution means more efforts to define ROI of the target areas and more ROIs to a VOI. It makes 3D segmentation the most time consuming job during image quantization.